The propagation kinetics of ethyl methacrylate (EMA) and ethyl α-hydroxy methacrylate (EHMA) has been subject to a computational study to understand their free radical polymerization (FRP) behavior in bulk and in solution using Density Functional Theory (DFT).
This analysis would reveal the cause of the significant correlation between computational and subjects' memory recalls shown in the above section.
The second cluster (indicated by green color) consisted of computational
The EEG theta modulation, that gates 50% of the input sequence, is not a cause of the significant correlation between computational and subjects' recalls, because significant correlation was still obtained without EEG theta modulation (data not shown).
Also, the optimal numerical parameters, minimizing computational cost subject to a specified error tolerance, are estimated.
The reason for avoiding this approach is both its structural (many antennas) and computational (decoding subject to partial brute-force) complexity.
Together with the clustering result of similarity between computational and subject's recalls (Fig. 3b), the current finding showed that theta phase precession can exist in the human brain and produces a better predictor of the subsequent recall than other traditional predictors.
We fit a computational model to subjects' choice data and examined the effects of citalopram and levodopa on the model parameters.
All answers were recorded, transcribed, and subjected to computational linguistic and content analyses.
The algorithm constitutes the core of an integrative, image-based computational framework for subject-specific simulation of the breathing lung.
